7 citations · 8 across the 9 of their papers we have counts for
11 papers
OpenMASC: An Open-Source Pipeline for Cross-Trajectory Metal-Aware Sampling and Correction in Accelerated MRI
Zhengyi Lu, Ming Lu, Chongyu Qu +11
Metal implants corrupt MRI measurements throughout -space, yet existing accelerated MRI methods assume clean data and most metal artifact reduction approaches assume fully sampl…
MASC: Metal-Aware Sampling and Correction via Reinforcement Learning for Accelerated MRI
Zhengyi Lu, Ming Lu, Chongyu Qu +11
Metal implants in MRI cause severe artifacts that degrade image quality and hinder clinical diagnosis. Traditional approaches address metal artifact reduction (MAR) and accelerated…
AdaFuse: Adaptive Multimodal Fusion for Lung Cancer Risk Prediction via Reinforcement Learning
Chongyu Qu, Zhengyi Lu, Yuxiang Lai +10
Multimodal fusion has emerged as a promising paradigm for disease diagnosis and prognosis, integrating complementary information from heterogeneous data sources such as medical ima…
Fast Electromagnetic and RF Circuit Co-Simulation for Passive Resonator Field Calculation and Optimization in MRI
Zhonghao Zhang, Ming Lu, Hao Liang +5
Passive resonators have been widely used in MRI to manipulate RF field distributions. However, optimizing these structures using full-wave electromagnetic simulations is computatio…
DeepAndes: A Self-Supervised Vision Foundation Model for Multi-Spectral Remote Sensing Imagery of the Andes
Junlin Guo, James R. Zimmer-Dauphinee, Jordan M. Nieusma +16
By mapping sites at large scales using remotely sensed data, archaeologists can generate unique insights into long-term demographic trends, inter-regional social networks, and past…
Sparse Measurement Medical CT Reconstruction using Multi-Fused Block Matching Denoising Priors
Maliha Hossain, Yuankai Huo, Xinqiang Yan +1
A major challenge for medical X-ray CT imaging is reducing the number of X-ray projections to lower radiation dosage and reduce scan times without compromising image quality. Howev…
Scale-up Unlearnable Examples Learning with High-Performance Computing
Yanfan Zhu, Issac Lyngaas, Murali Gopalakrishnan Meena +8
Recent advancements in AI models are structured to retain user interactions, which could inadvertently include sensitive healthcare data. In the healthcare field, particularly when…
Fast-RF-Shimming: Accelerate RF Shimming in 7T MRI using Deep Learning
Zhengyi Lu, Hao Liang, Ming Lu +3
Ultrahigh field (UHF) Magnetic Resonance Imaging (MRI) offers an elevated signal-to-noise ratio (SNR), enabling exceptionally high spatial resolution that benefits both clinical di…
Optimizing Transmit Field Inhomogeneity of Parallel RF Transmit Design in 7T MRI using Deep Learning
Zhengyi Lu, Hao Liang, Xiao Wang +2
Ultrahigh field (UHF) Magnetic Resonance Imaging (MRI) provides a higher signal-to-noise ratio and, thereby, higher spatial resolution. However, UHF MRI introduces challenges such…
Vision Foundation Models in Remote Sensing: A Survey
Siqi Lu, Junlin Guo, James R Zimmer-Dauphinee +5
Artificial Intelligence (AI) technologies have profoundly transformed the field of remote sensing, revolutionizing data collection, processing, and analysis. Traditionally reliant…
Adaptive Patching for High-resolution Image Segmentation with Transformers
Enzhi Zhang, Isaac Lyngaas, Peng Chen +5
Attention-based models are proliferating in the space of image analytics, including segmentation. The standard method of feeding images to transformer encoders is to divide the ima…